Community for Data Integration (CDI)
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The Community for Data Integration (CDI) is a dynamic community of practice working together to grow USGS knowledge and capacity in scientific data and information management and integration.
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Join a group of peers to explore common interests and solve shared challenges.
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The CDI supports innovative ideas across the community with seed funding for projects.
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Participate in monthly forums, topical discussions, trainings, or the annual proposals process.
Join us!News
Help Choose the Next Round of CDI Projects - FY20 Statements are In!
Phase 1 of the FY20 Community for Data Integration Request for Proposals asks for community members to ask questions and make suggestions to the project teams.
Congratulations to the 2019 CDI Funded Projects
The Community for Data Integration has announced fourteen proposals to be funded in FY2019. This year’s request for proposals focused on the themes of biosurveillance, FAIR (findable, accessible, interoperable, and reusable) data, national data assets, and reusable tools.
From Big Data to Smart Data: 2019 CDI Workshop Registration is Open
Registration is open for our 2019 Community for Data Integration Workshop, "From Big Data to Smart Data."
Publications
Community for Data Integration fiscal year 2017 funded project report
The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 11 projects funded in fiscal year 2017, outlining their goals, activities, and outputs.
Hsu, Leslie; Allstadt, Kate E.; Bell, Tara M.; Boydston, Erin E.; Erickson, Richard A.; Everette, A. Lance; Lentz, Erika E.; Peters, Jeff; Reichert, Brian E.; Nagorsen, Sarah; Sherba, Jason T.; Signell, Richard P.; Wiltermuth, Mark T.; Young, John A.
Wrangling distributed computing for high-throughput environmental science: An introduction to HTCondor
Biologists and environmental scientists now routinely solve computational problems that were unimaginable a generation ago. Examples include processing geospatial data, analyzing -omics data, and running large-scale simulations. Conventional desktop computing cannot handle these tasks when they are large, and high-performance computing is not...
Erickson, Richard A.; Fienen, Michael N.; McCalla, S. Grace; Weiser, Emily L.; Bower, Melvin L.; Knudson, Jonathan M.; Thain, Greg
Community for Data Integration 2017 annual report
The Community for Data Integration (CDI) is a group that helps members grow their expertise on all aspects of working with scientific data. The CDI’s activities advance data and information integration capabilities in the U.S. Geological Survey and in the wider Earth and biological sciences. This annual report describes the presentations,...
Hsu, Leslie; Langseth, Madison L.